Overview

Dataset statistics

Number of variables13
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory108.5 B

Variable types

Categorical5
Text7
Numeric1

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,설립유형,교실수,교실면적,체육장,보건/위생공간,조리실/급식공간,기타공간,공시차수,주소
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-20648/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
교육지원청명 has constant value ""Constant
설립유형 is highly overall correlated with 체육장High correlation
체육장 is highly overall correlated with 설립유형High correlation
유치원코드 has unique valuesUnique
유치원명 has unique valuesUnique

Reproduction

Analysis started2024-03-13 08:16:38.109220
Analysis finished2024-03-13 08:16:38.973692
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
서울특별시교육청
38 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시교육청
2nd row서울특별시교육청
3rd row서울특별시교육청
4th row서울특별시교육청
5th row서울특별시교육청

Common Values

ValueCountFrequency (%)
서울특별시교육청 38
100.0%

Length

2024-03-13T17:16:39.054164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:16:39.161812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 38
100.0%

교육지원청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
동작관악교육지원청
38 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동작관악교육지원청
2nd row동작관악교육지원청
3rd row동작관악교육지원청
4th row동작관악교육지원청
5th row동작관악교육지원청

Common Values

ValueCountFrequency (%)
동작관악교육지원청 38
100.0%

Length

2024-03-13T17:16:39.253516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:16:39.338843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동작관악교육지원청 38
100.0%

유치원코드
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T17:16:39.513163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters1368
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row1ecec08d-0562-b044-e053-0a32095ab044
2nd row1ecec08d-08f9-b044-e053-0a32095ab044
3rd row1ecec08d-09b9-b044-e053-0a32095ab044
4th row1ecec08d-09ba-b044-e053-0a32095ab044
5th row1fc6dd86-cccc-d1d2-e053-0a32095ad1d2
ValueCountFrequency (%)
1ecec08d-0562-b044-e053-0a32095ab044 1
 
2.6%
1ecec08d-0561-b044-e053-0a32095ab044 1
 
2.6%
8a1d9a31-65ba-4f9e-b5dd-dc6a8169ce73 1
 
2.6%
1ecec08c-f8ac-b044-e053-0a32095ab044 1
 
2.6%
1ecec08c-f940-b044-e053-0a32095ab044 1
 
2.6%
1ecec08c-fc3a-b044-e053-0a32095ab044 1
 
2.6%
1ecec08c-feb1-b044-e053-0a32095ab044 1
 
2.6%
1ecec08d-0147-b044-e053-0a32095ab044 1
 
2.6%
1ecec08d-04ca-b044-e053-0a32095ab044 1
 
2.6%
1ecec08d-0091-b044-e053-0a32095ab044 1
 
2.6%
Other values (28) 28
73.7%
2024-03-13T17:16:39.828615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 217
15.9%
- 152
11.1%
4 141
10.3%
e 116
8.5%
c 108
7.9%
a 85
 
6.2%
b 81
 
5.9%
3 81
 
5.9%
5 76
 
5.6%
1 55
 
4.0%
Other values (7) 256
18.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 751
54.9%
Lowercase Letter 465
34.0%
Dash Punctuation 152
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 217
28.9%
4 141
18.8%
3 81
 
10.8%
5 76
 
10.1%
1 55
 
7.3%
8 52
 
6.9%
9 51
 
6.8%
2 46
 
6.1%
6 24
 
3.2%
7 8
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
e 116
24.9%
c 108
23.2%
a 85
18.3%
b 81
17.4%
f 38
 
8.2%
d 37
 
8.0%
Dash Punctuation
ValueCountFrequency (%)
- 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 903
66.0%
Latin 465
34.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 217
24.0%
- 152
16.8%
4 141
15.6%
3 81
 
9.0%
5 76
 
8.4%
1 55
 
6.1%
8 52
 
5.8%
9 51
 
5.6%
2 46
 
5.1%
6 24
 
2.7%
Latin
ValueCountFrequency (%)
e 116
24.9%
c 108
23.2%
a 85
18.3%
b 81
17.4%
f 38
 
8.2%
d 37
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 217
15.9%
- 152
11.1%
4 141
10.3%
e 116
8.5%
c 108
7.9%
a 85
 
6.2%
b 81
 
5.9%
3 81
 
5.9%
5 76
 
5.6%
1 55
 
4.0%
Other values (7) 256
18.7%

유치원명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T17:16:40.020677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length5
Mean length7.2631579
Min length5

Characters and Unicode

Total characters276
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row노량진교회유치원
2nd row상아유치원
3rd row소망유치원
4th row승혜유치원
5th row행복한숲유치원
ValueCountFrequency (%)
노량진교회유치원 1
 
2.6%
강남유치원 1
 
2.6%
서울은로유치원 1
 
2.6%
양문유치원 1
 
2.6%
샛별유치원 1
 
2.6%
벧엘유치원 1
 
2.6%
서울남성초등학교병설유치원 1
 
2.6%
열림유치원 1
 
2.6%
서울신남성초등학교병설유치원 1
 
2.6%
상도유치원 1
 
2.6%
Other values (28) 28
73.7%
2024-03-13T17:16:40.363056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 38
 
13.8%
치 38
 
13.8%
원 38
 
13.8%
서 10
 
3.6%
울 10
 
3.6%
교 9
 
3.3%
설 8
 
2.9%
병 8
 
2.9%
학 8
 
2.9%
등 8
 
2.9%
Other values (59) 101
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 276
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 38
 
13.8%
치 38
 
13.8%
원 38
 
13.8%
서 10
 
3.6%
울 10
 
3.6%
교 9
 
3.3%
설 8
 
2.9%
병 8
 
2.9%
학 8
 
2.9%
등 8
 
2.9%
Other values (59) 101
36.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 276
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 38
 
13.8%
치 38
 
13.8%
원 38
 
13.8%
서 10
 
3.6%
울 10
 
3.6%
교 9
 
3.3%
설 8
 
2.9%
병 8
 
2.9%
학 8
 
2.9%
등 8
 
2.9%
Other values (59) 101
36.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 276
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 38
 
13.8%
치 38
 
13.8%
원 38
 
13.8%
서 10
 
3.6%
울 10
 
3.6%
교 9
 
3.3%
설 8
 
2.9%
병 8
 
2.9%
학 8
 
2.9%
등 8
 
2.9%
Other values (59) 101
36.6%

설립유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
사립(사인)
19 
사립(법인)
9 
공립(병설)
8 
공립(단설)
2 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사립(법인)
2nd row사립(사인)
3rd row사립(사인)
4th row사립(사인)
5th row사립(사인)

Common Values

ValueCountFrequency (%)
사립(사인) 19
50.0%
사립(법인) 9
23.7%
공립(병설) 8
21.1%
공립(단설) 2
 
5.3%

Length

2024-03-13T17:16:40.480861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:16:40.584712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 19
50.0%
사립(법인 9
23.7%
공립(병설 8
21.1%
공립(단설 2
 
5.3%

교실수
Categorical

Distinct13
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
5개
8 
3개
6 
6개
6 
7개
5 
13개
3 
Other values (8)
10 

Length

Max length3
Median length2
Mean length2.1578947
Min length2

Unique

Unique6 ?
Unique (%)15.8%

Sample

1st row3개
2nd row2개
3rd row3개
4th row5개
5th row6개

Common Values

ValueCountFrequency (%)
5개 8
21.1%
3개 6
15.8%
6개 6
15.8%
7개 5
13.2%
13개 3
 
7.9%
1개 2
 
5.3%
8개 2
 
5.3%
2개 1
 
2.6%
12개 1
 
2.6%
10개 1
 
2.6%
Other values (3) 3
 
7.9%

Length

2024-03-13T17:16:40.926330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5개 8
21.1%
3개 6
15.8%
6개 6
15.8%
7개 5
13.2%
13개 3
 
7.9%
1개 2
 
5.3%
8개 2
 
5.3%
2개 1
 
2.6%
12개 1
 
2.6%
10개 1
 
2.6%
Other values (3) 3
 
7.9%

교실면적
Text

Distinct35
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T17:16:41.095092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9736842
Min length3

Characters and Unicode

Total characters151
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)84.2%

Sample

1st row164㎡
2nd row1777㎡
3rd row319㎡
4th row297㎡
5th row320㎡
ValueCountFrequency (%)
66㎡ 2
 
5.3%
300㎡ 2
 
5.3%
260㎡ 2
 
5.3%
164㎡ 1
 
2.6%
395㎡ 1
 
2.6%
875㎡ 1
 
2.6%
416㎡ 1
 
2.6%
264㎡ 1
 
2.6%
540㎡ 1
 
2.6%
351㎡ 1
 
2.6%
Other values (25) 25
65.8%
2024-03-13T17:16:41.414167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 38
25.2%
2 17
11.3%
6 13
 
8.6%
0 13
 
8.6%
3 13
 
8.6%
5 11
 
7.3%
4 11
 
7.3%
7 10
 
6.6%
8 10
 
6.6%
1 8
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 113
74.8%
Other Symbol 38
 
25.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17
15.0%
6 13
11.5%
0 13
11.5%
3 13
11.5%
5 11
9.7%
4 11
9.7%
7 10
8.8%
8 10
8.8%
1 8
7.1%
9 7
6.2%
Other Symbol
ValueCountFrequency (%)
㎡ 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 151
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 38
25.2%
2 17
11.3%
6 13
 
8.6%
0 13
 
8.6%
3 13
 
8.6%
5 11
 
7.3%
4 11
 
7.3%
7 10
 
6.6%
8 10
 
6.6%
1 8
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113
74.8%
CJK Compat 38
 
25.2%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 38
100.0%
ASCII
ValueCountFrequency (%)
2 17
15.0%
6 13
11.5%
0 13
11.5%
3 13
11.5%
5 11
9.7%
4 11
9.7%
7 10
8.8%
8 10
8.8%
1 8
7.1%
9 7
6.2%

체육장
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
㎡
21 
132㎡
 
2
311㎡
 
1
69㎡
 
1
84㎡
 
1
Other values (12)
12 

Length

Max length5
Median length1
Mean length2.2105263
Min length1

Unique

Unique15 ?
Unique (%)39.5%

Sample

1st row㎡
2nd row㎡
3rd row㎡
4th row㎡
5th row㎡

Common Values

ValueCountFrequency (%)
㎡ 21
55.3%
132㎡ 2
 
5.3%
311㎡ 1
 
2.6%
69㎡ 1
 
2.6%
84㎡ 1
 
2.6%
0㎡ 1
 
2.6%
272㎡ 1
 
2.6%
200㎡ 1
 
2.6%
66㎡ 1
 
2.6%
267㎡ 1
 
2.6%
Other values (7) 7
 
18.4%

Length

2024-03-13T17:16:41.550874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
㎡ 21
55.3%
132㎡ 2
 
5.3%
267㎡ 1
 
2.6%
222㎡ 1
 
2.6%
226㎡ 1
 
2.6%
72㎡ 1
 
2.6%
209㎡ 1
 
2.6%
1599㎡ 1
 
2.6%
167㎡ 1
 
2.6%
66㎡ 1
 
2.6%
Other values (7) 7
 
18.4%

보건/위생공간
Text

Distinct32
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T17:16:41.703704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1842105
Min length2

Characters and Unicode

Total characters121
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)73.7%

Sample

1st row20㎡
2nd row140㎡
3rd row30㎡
4th row0㎡
5th row60㎡
ValueCountFrequency (%)
0㎡ 4
 
10.5%
30㎡ 2
 
5.3%
80㎡ 2
 
5.3%
20㎡ 2
 
5.3%
25㎡ 1
 
2.6%
116㎡ 1
 
2.6%
400㎡ 1
 
2.6%
68㎡ 1
 
2.6%
110㎡ 1
 
2.6%
83㎡ 1
 
2.6%
Other values (22) 22
57.9%
2024-03-13T17:16:41.999118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 38
31.4%
0 20
16.5%
1 15
 
12.4%
4 10
 
8.3%
6 9
 
7.4%
2 7
 
5.8%
8 6
 
5.0%
3 6
 
5.0%
7 5
 
4.1%
5 5
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
68.6%
Other Symbol 38
31.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
24.1%
1 15
18.1%
4 10
12.0%
6 9
10.8%
2 7
 
8.4%
8 6
 
7.2%
3 6
 
7.2%
7 5
 
6.0%
5 5
 
6.0%
Other Symbol
ValueCountFrequency (%)
㎡ 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 38
31.4%
0 20
16.5%
1 15
 
12.4%
4 10
 
8.3%
6 9
 
7.4%
2 7
 
5.8%
8 6
 
5.0%
3 6
 
5.0%
7 5
 
4.1%
5 5
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
68.6%
CJK Compat 38
31.4%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 38
100.0%
ASCII
ValueCountFrequency (%)
0 20
24.1%
1 15
18.1%
4 10
12.0%
6 9
10.8%
2 7
 
8.4%
8 6
 
7.2%
3 6
 
7.2%
7 5
 
6.0%
5 5
 
6.0%

조리실/급식공간
Text

Distinct35
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T17:16:42.193552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.4736842
Min length2

Characters and Unicode

Total characters132
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)86.8%

Sample

1st row386㎡
2nd row0㎡
3rd row5㎡
4th row136㎡
5th row104㎡
ValueCountFrequency (%)
0㎡ 3
 
7.9%
66㎡ 2
 
5.3%
36㎡ 1
 
2.6%
63㎡ 1
 
2.6%
721㎡ 1
 
2.6%
426㎡ 1
 
2.6%
300㎡ 1
 
2.6%
90㎡ 1
 
2.6%
1640㎡ 1
 
2.6%
9㎡ 1
 
2.6%
Other values (25) 25
65.8%
2024-03-13T17:16:42.522571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 38
28.8%
6 16
12.1%
1 15
 
11.4%
0 13
 
9.8%
2 12
 
9.1%
3 11
 
8.3%
4 9
 
6.8%
5 5
 
3.8%
7 5
 
3.8%
8 4
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94
71.2%
Other Symbol 38
28.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 16
17.0%
1 15
16.0%
0 13
13.8%
2 12
12.8%
3 11
11.7%
4 9
9.6%
5 5
 
5.3%
7 5
 
5.3%
8 4
 
4.3%
9 4
 
4.3%
Other Symbol
ValueCountFrequency (%)
㎡ 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 132
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 38
28.8%
6 16
12.1%
1 15
 
11.4%
0 13
 
9.8%
2 12
 
9.1%
3 11
 
8.3%
4 9
 
6.8%
5 5
 
3.8%
7 5
 
3.8%
8 4
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94
71.2%
CJK Compat 38
28.8%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 38
100.0%
ASCII
ValueCountFrequency (%)
6 16
17.0%
1 15
16.0%
0 13
13.8%
2 12
12.8%
3 11
11.7%
4 9
9.6%
5 5
 
5.3%
7 5
 
5.3%
8 4
 
4.3%
9 4
 
4.3%

기타공간
Text

Distinct30
Distinct (%)78.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T17:16:42.682343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1315789
Min length2

Characters and Unicode

Total characters119
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)65.8%

Sample

1st row16㎡
2nd row0㎡
3rd row5㎡
4th row10㎡
5th row20㎡
ValueCountFrequency (%)
0㎡ 4
 
10.5%
10㎡ 3
 
7.9%
16㎡ 2
 
5.3%
14㎡ 2
 
5.3%
18㎡ 2
 
5.3%
24㎡ 1
 
2.6%
400㎡ 1
 
2.6%
190㎡ 1
 
2.6%
30㎡ 1
 
2.6%
112㎡ 1
 
2.6%
Other values (20) 20
52.6%
2024-03-13T17:16:42.969523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 38
31.9%
1 21
17.6%
0 18
15.1%
2 9
 
7.6%
4 8
 
6.7%
5 6
 
5.0%
9 6
 
5.0%
6 5
 
4.2%
3 4
 
3.4%
8 3
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
68.1%
Other Symbol 38
31.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
25.9%
0 18
22.2%
2 9
11.1%
4 8
 
9.9%
5 6
 
7.4%
9 6
 
7.4%
6 5
 
6.2%
3 4
 
4.9%
8 3
 
3.7%
7 1
 
1.2%
Other Symbol
ValueCountFrequency (%)
㎡ 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 38
31.9%
1 21
17.6%
0 18
15.1%
2 9
 
7.6%
4 8
 
6.7%
5 6
 
5.0%
9 6
 
5.0%
6 5
 
4.2%
3 4
 
3.4%
8 3
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
68.1%
CJK Compat 38
31.9%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 38
100.0%
ASCII
ValueCountFrequency (%)
1 21
25.9%
0 18
22.2%
2 9
11.1%
4 8
 
9.9%
5 6
 
7.4%
9 6
 
7.4%
6 5
 
6.2%
3 4
 
4.9%
8 3
 
3.7%
7 1
 
1.2%

공시차수
Real number (ℝ)

Distinct6
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20221.263
Minimum20181
Maximum20231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-03-13T17:16:43.077766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20181
5-th percentile20181
Q120221
median20231
Q320231
95-th percentile20231
Maximum20231
Range50
Interquartile range (IQR)10

Descriptive statistics

Standard deviation16.843772
Coefficient of variation (CV)0.00083297329
Kurtosis0.81308066
Mean20221.263
Median Absolute Deviation (MAD)0
Skewness-1.5120845
Sum768408
Variance283.71266
MonotonicityNot monotonic
2024-03-13T17:16:43.164531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20231 26
68.4%
20181 3
 
7.9%
20221 3
 
7.9%
20201 3
 
7.9%
20191 2
 
5.3%
20211 1
 
2.6%
ValueCountFrequency (%)
20181 3
 
7.9%
20191 2
 
5.3%
20201 3
 
7.9%
20211 1
 
2.6%
20221 3
 
7.9%
20231 26
68.4%
ValueCountFrequency (%)
20231 26
68.4%
20221 3
 
7.9%
20211 1
 
2.6%
20201 3
 
7.9%
20191 2
 
5.3%
20181 3
 
7.9%

주소
Text

Distinct36
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T17:16:43.377535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21.5
Mean length18.789474
Min length16

Characters and Unicode

Total characters714
Distinct characters57
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)89.5%

Sample

1st row서울특별시 동작구 노량진로30길 9
2nd row서울특별시 동작구 양녕로26길 15
3rd row서울특별시 동작구 현충로 119
4th row서울특별시 동작구 성대로21길 15
5th row서울특별시 동작구 만양로 26
ValueCountFrequency (%)
서울특별시 38
25.0%
동작구 38
25.0%
15 3
 
2.0%
서달로 2
 
1.3%
115 2
 
1.3%
만양로3길 2
 
1.3%
48 2
 
1.3%
47 2
 
1.3%
현충로 2
 
1.3%
사당로 2
 
1.3%
Other values (58) 59
38.8%
2024-03-13T17:16:43.726594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
16.0%
서 40
 
5.6%
동 40
 
5.6%
작 40
 
5.6%
시 39
 
5.5%
특 38
 
5.3%
별 38
 
5.3%
구 38
 
5.3%
울 38
 
5.3%
로 36
 
5.0%
Other values (47) 253
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 466
65.3%
Decimal Number 128
 
17.9%
Space Separator 114
 
16.0%
Dash Punctuation 6
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 40
8.6%
동 40
8.6%
작 40
8.6%
시 39
8.4%
특 38
 
8.2%
별 38
 
8.2%
구 38
 
8.2%
울 38
 
8.2%
로 36
 
7.7%
길 24
 
5.2%
Other values (35) 95
20.4%
Decimal Number
ValueCountFrequency (%)
1 25
19.5%
4 21
16.4%
2 18
14.1%
5 14
10.9%
3 13
10.2%
6 13
10.2%
0 7
 
5.5%
7 7
 
5.5%
8 5
 
3.9%
9 5
 
3.9%
Space Separator
ValueCountFrequency (%)
114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 466
65.3%
Common 248
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 40
8.6%
동 40
8.6%
작 40
8.6%
시 39
8.4%
특 38
 
8.2%
별 38
 
8.2%
구 38
 
8.2%
울 38
 
8.2%
로 36
 
7.7%
길 24
 
5.2%
Other values (35) 95
20.4%
Common
ValueCountFrequency (%)
114
46.0%
1 25
 
10.1%
4 21
 
8.5%
2 18
 
7.3%
5 14
 
5.6%
3 13
 
5.2%
6 13
 
5.2%
0 7
 
2.8%
7 7
 
2.8%
- 6
 
2.4%
Other values (2) 10
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 466
65.3%
ASCII 248
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
46.0%
1 25
 
10.1%
4 21
 
8.5%
2 18
 
7.3%
5 14
 
5.6%
3 13
 
5.2%
6 13
 
5.2%
0 7
 
2.8%
7 7
 
2.8%
- 6
 
2.4%
Other values (2) 10
 
4.0%
Hangul
ValueCountFrequency (%)
서 40
8.6%
동 40
8.6%
작 40
8.6%
시 39
8.4%
특 38
 
8.2%
별 38
 
8.2%
구 38
 
8.2%
울 38
 
8.2%
로 36
 
7.7%
길 24
 
5.2%
Other values (35) 95
20.4%

Interactions

2024-03-13T17:16:38.637584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T17:16:43.817809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원코드유치원명설립유형교실수교실면적체육장보건/위생공간조리실/급식공간기타공간공시차수주소
유치원코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
유치원명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설립유형1.0001.0001.0000.5810.9660.8681.0001.0000.8630.0000.000
교실수1.0001.0000.5811.0000.9860.6670.9770.6580.8380.0000.000
교실면적1.0001.0000.9660.9861.0000.9490.9170.9950.9370.0000.946
체육장1.0001.0000.8680.6670.9491.0000.9580.9850.9610.0000.000
보건/위생공간1.0001.0001.0000.9770.9170.9581.0000.9340.9680.0000.912
조리실/급식공간1.0001.0001.0000.6580.9950.9850.9341.0000.9840.0000.946
기타공간1.0001.0000.8630.8380.9370.9610.9680.9841.0000.0000.934
공시차수1.0001.0000.0000.0000.0000.0000.0000.0000.0001.0000.716
주소1.0001.0000.0000.0000.9460.0000.9120.9460.9340.7161.000
2024-03-13T17:16:43.942076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립유형체육장교실수
설립유형1.0000.5390.313
체육장0.5391.0000.249
교실수0.3130.2491.000
2024-03-13T17:16:44.019068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공시차수설립유형교실수체육장
공시차수1.0000.0000.0000.000
설립유형0.0001.0000.3130.539
교실수0.0000.3131.0000.249
체육장0.0000.5390.2491.000

Missing values

2024-03-13T17:16:38.747669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T17:16:38.901878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

교육청명교육지원청명유치원코드유치원명설립유형교실수교실면적체육장보건/위생공간조리실/급식공간기타공간공시차수주소
0서울특별시교육청동작관악교육지원청1ecec08d-0562-b044-e053-0a32095ab044노량진교회유치원사립(법인)3개164㎡㎡20㎡386㎡16㎡20231서울특별시 동작구 노량진로30길 9
1서울특별시교육청동작관악교육지원청1ecec08d-08f9-b044-e053-0a32095ab044상아유치원사립(사인)2개1777㎡㎡140㎡0㎡0㎡20231서울특별시 동작구 양녕로26길 15
2서울특별시교육청동작관악교육지원청1ecec08d-09b9-b044-e053-0a32095ab044소망유치원사립(사인)3개319㎡㎡30㎡5㎡5㎡20231서울특별시 동작구 현충로 119
3서울특별시교육청동작관악교육지원청1ecec08d-09ba-b044-e053-0a32095ab044승혜유치원사립(사인)5개297㎡㎡0㎡136㎡10㎡20231서울특별시 동작구 성대로21길 15
4서울특별시교육청동작관악교육지원청1fc6dd86-cccc-d1d2-e053-0a32095ad1d2행복한숲유치원사립(사인)6개320㎡㎡60㎡104㎡20㎡20231서울특별시 동작구 만양로 26
5서울특별시교육청동작관악교육지원청3f6c4638-fa48-42ee-b862-cdcbdee6eef0서울노량진초등학교병설유치원공립(병설)1개66㎡66㎡17㎡132㎡132㎡20231서울특별시 동작구 장승배기로 160
6서울특별시교육청동작관악교육지원청6f1822d8-a14e-4236-a707-fd9af1e88aec시현유치원사립(사인)6개300㎡㎡27㎡0㎡10㎡20231서울특별시 동작구 만양로8길 50
7서울특별시교육청동작관악교육지원청89e2307e-5deb-45c1-84c3-670f209825f3서울행림초등학교병설유치원공립(병설)3개225㎡69㎡66㎡217㎡14㎡20231서울특별시 동작구 솔밭로 47
8서울특별시교육청동작관악교육지원청1ecec08d-0090-b044-e053-0a32095ab044동아유치원사립(사인)12개745㎡132㎡143㎡26㎡501㎡20181서울특별시 동작구 만양로3길 48
9서울특별시교육청동작관악교육지원청1ecec08c-efbf-b044-e053-0a32095ab044서울은로초등학교병설유치원공립(병설)5개304㎡84㎡64㎡231㎡18㎡20221서울특별시 동작구 서달로 115
교육청명교육지원청명유치원코드유치원명설립유형교실수교실면적체육장보건/위생공간조리실/급식공간기타공간공시차수주소
28서울특별시교육청동작관악교육지원청1ecec08c-fc36-b044-e053-0a32095ab044사랑유치원사립(사인)6개248㎡167㎡40㎡9㎡112㎡20201서울특별시 동작구 여의대방로24나길 6
29서울특별시교육청동작관악교육지원청1ecec08d-0091-b044-e053-0a32095ab044상도유치원사립(법인)3개192㎡㎡25㎡10㎡24㎡20201서울특별시 동작구 상도로47길 53
30서울특별시교육청동작관악교육지원청1ecec08d-04c9-b044-e053-0a32095ab044메이플유치원사립(사인)6개260㎡㎡45㎡20㎡191㎡20201서울특별시 동작구 여의대방로 22
31서울특별시교육청동작관악교육지원청1ecec08d-09bb-b044-e053-0a32095ab044요요유치원사립(사인)8개486㎡㎡83㎡346㎡18㎡20231서울특별시 동작구 여의대방로 28
32서울특별시교육청동작관악교육지원청1ecec08d-0a6c-b044-e053-0a32095ab044서울강남초등학교병설유치원공립(병설)4개473㎡1599㎡48㎡96㎡16㎡20231서울특별시 동작구 강남초등길 15
33서울특별시교육청동작관악교육지원청1ecec08d-0bb2-b044-e053-0a32095ab044중앙대부속유치원사립(법인)7개684㎡209㎡217㎡1462㎡61㎡20231서울특별시 동작구 흑석로 47
34서울특별시교육청동작관악교육지원청1ecec08d-0d67-b044-e053-0a32095ab044명수유치원사립(법인)5개260㎡㎡14㎡152㎡9㎡20231서울특별시 동작구 흑석로13길 3
35서울특별시교육청동작관악교육지원청1ecec08d-0e1f-b044-e053-0a32095ab044송림유치원사립(법인)7개238㎡72㎡20㎡38㎡35㎡20231서울특별시 동작구 사당로2다길 95
36서울특별시교육청동작관악교육지원청8a1d9a31-65ba-4f9e-b5dd-dc6a8169ce73서울은로유치원공립(단설)11개586㎡226㎡136㎡1164㎡194㎡20231서울특별시 동작구 서달로 115
37서울특별시교육청동작관악교육지원청afaeef71-68b6-4a13-acd4-cb8285459fb9서울본동초등학교병설유치원공립(병설)1개66㎡663㎡104㎡66㎡426㎡20221서울특별시 동작구 노량진로26길 16-40